{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3293dc77-0617-41cc-bd6b-3dbf8906fadf",
   "metadata": {},
   "source": [
    "# Graphing Decision Trees and Decision Boundaries\n",
    "\n",
    "### We'll explore various ways to calculate decision tree splits. A decision tree will tell us how to navigate our features to arrive at a decision, whereas a decision boundary will show us how those features split."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2aa4822c-e9f7-4dfa-8c71-e09cc65e10e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import _plotting\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import pandas\n",
    "import sklearn.tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "395e9700-88c7-4909-966d-484884d8f06b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x165393c81f0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAD4CAYAAAD1jb0+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAATRElEQVR4nO3dfYzW5Z3v8fd3eRB07OLC9EFwF5pWagsstqP4dIgKa3dXI+3J1mpSs9JtPN0WV+1JNl1z2nLIqTnHbja7+seu+NystrbUpgtpmhqE7iGh2AGpCtjjdrVlfGJkRcqWCVP4nj/mnimODDD3fc/87mvm/UomzFz3Pffvkwl8uOa6f7/fFZmJJKk8v1N1AElSfSxwSSqUBS5JhbLAJalQFrgkFWriaB5sxowZOXv27NE8pCQVb+vWra9nZvvg8VEt8NmzZ9PZ2Tmah5Sk4kXEL4417hKKJBXKApekQlngklQoC1ySCmWBS1KhTngWSkTcD1wF7MnMebWx3wMeBWYDLwLXZOYbIxdTkoZw+0w4dODt45Pb4LaXRj/PKDqZGfiDwB8PGvsisD4z3w+sr30tSaPvWOV9vPEx5IQFnpn/CvzHoOFlwEO1zx8CPtbcWJKkE6l3DfxdmflK7fNXgXcN9cSIuDEiOiOis7u7u87DSZIGa/hNzOzbEWLIXSEyc3VmdmRmR3v7264ElSTVqd4Cfy0i3gNQ+3NP8yJJkk5GvQX+L8Cf1z7/c+B7zYkjScM0uW1442PIyZxG+A3gUmBGRHQBXwH+N/CtiPgL4BfANSMZUpKGNMZPFTyeExZ4Zl43xENLmpxFkjQMXokpSYWywCWpUBa4JBXKApekQlngklQoC1ySCmWBS1KhLHBJKpQFLkmFssAlqVAWuCQVygKXpEJZ4JJUqBPejbBS43i3aUk6kdaegY/j3aYl6URau8AlSUOywCWpUBa4JBXKApekQrV2gY/j3aYl6URa+zRCTxWUpCG19gxckjQkC1ySCmWBS1KhLHBJKpQFLkmFssAlqVAWuCQVygKXpEJZ4JJUKAtckgplgUtSoSxwSSqUBS5JhbLAJalQDd1ONiJuBT4DJPAMsDwze5oRTFKLuX3msTcUn9zmrZ8rUvcMPCJmAn8FdGTmPGACcG2zgklqMccq7+ONa8Q1uoQyEZgaEROBU4GXG48kSToZdRd4Zr4E/C3wS+AV4M3M/OHg50XEjRHRGRGd3d3d9SeVJL1FI0soZwDLgDnAmcBpEfGpwc/LzNWZ2ZGZHe3t7fUnlSS9RSNLKEuBFzKzOzN7gceAi5oTS5J0Io0U+C+BCyLi1IgIYAmwqzmxJLWcyW3DG9eIq/s0wszcEhFrgG3Ab4CngNXNCiapxXiqYMtp6DzwzPwK8JUmZZEkDYNXYkpSoSxwSSqUBS5JhbLAJalQFrgkFcoCl6RCWeCSVCgLXJIKZYFLUqEscEkqlAUuSYWywCWpUBa4JBXKAteo2bO/h8V3bGDPr3qqjiKNCRa4Rs2d659n9xu/5s71/1Z1FGlMsMA1Kvbs7+HbW7vIhDWdu52FS01ggWtU3Ln+eY5kAnA401m41AQWuEZc/+y793BfgfceTmfhUhNY4BpxR8+++zkLlxpngWvEPb7rtYHZd7/ew8njO1+tKJE0NjS0qbF0MrbctrTqCNKY5AxckgplgUtSoSxwSSqUBS5JhbLAJalQFrgkFcoCl6RCWeCSVCgLXJIKZYFLUqEscEkqlAUuSYWywCWpUBa4JBWqodvJRsQ04F5gHpDApzNzcxNyFWHP/h7+7J82s+YvL+Sdp0+pOo6kVnL7TDh04O3jk9vgtpeacohGZ+D/APwgMz8A/CGwq/FI5XCXdUlDOlZ5H2+8DnUXeET8LrAYuA8gMw9l5r4m5Wp57rIuqWqNzMDnAN3AAxHxVETcGxGnDX5SRNwYEZ0R0dnd3d3A4VqLu6xLqlojBT4R+DDwj5l5LvCfwBcHPykzV2dmR2Z2tLe3N3C41uEu65JaQSMF3gV0ZeaW2tdr6Cv0Mc9d1iW1groLPDNfBXZHxNza0BJgZ1NStTh3WZd0QpPbhjdeh8hBM8lhfXPEQvpOI5wM/DuwPDPfGOr5HR0d2dnZWffxJGk8ioitmdkxeLyh88AzczvwtheVJI08r8SUpEJZ4JJUKAtckgplgUtSoSxwSSqUBS5JhbLAJalQFrgkFcoCl6RCWeCSVCgLXJIKZYFLUqEscEkqVEN3Ixwt7v6ucWUUdjPX2FDEDNzd3zWujMJu5hobWr7A3f1dko6t5Qvc3d8l6dhausDd/V2ShtbSBe7u75I0tJYucHd/17g0CruZa2xo6dMIt9y2tOoI0ujzVEGdpJaegUuShmaBS1KhLHBJKpQFLkmFssAlqVAWuCQVygKXpEJZ4JJUKAtckgplgUtSoSxwSSqUBS5JhbLAJalQFrgkFarh28lGxASgE3gpM69qPJIkDcPtM4+94fPktjF/a95mzMBvBnY14XUkafiOVd7HGx9DGirwiJgFXAnc25w4kqST1egM/O+BvwaODPWEiLgxIjojorO7u7vBw0mS+tVd4BFxFbAnM7ce73mZuTozOzKzo729vd7DSZIGaWQGfjFwdUS8CHwTuDwi/rkpqSRJJ1R3gWfm32TmrMycDVwLPJGZn2paMkk6GZPbhjc+hrT0rvSSdEJj/FTB42lKgWfmRmBjM15LknRyvBJTkgplgUtSoSxwSSqUBS5JhbLAJalQFrgkFcoCl6RCWeCSVCgLXJIKZYFLUqEscEkqlAUuSYWywCWpUBZ4A/bs72HxHRvY86ueqqNIGocs8Abcuf55dr/xa+5c/29VR5E0Dlngddqzv4dvb+0iE9Z07nYWLmnUWeB1unP98xzJBOBwprNwSaPOAq9D/+y793BfgfceTmfhkkadBV6Ho2ff/ZyFSxptFngdHt/12sDsu1/v4eTxna9WlEjSeOSu9HXYctvSqiNIkjNwSSqVBS5JhbLAJalQFrgkFcoCl6RCWeCSVCgLXJIKZYFLUqEscEkqlAUuSYWywCWpUJXfC6W3t5euri56erwV65QpU5g1axaTJk2qOoqkAlRe4F1dXZx++unMnj2biKg6TmUyk71799LV1cWcOXOqjiOpAJUvofT09DB9+vRxXd4AEcH06dP9TUTSSau7wCPirIjYEBE7I2JHRNzcwGvV+61jSrN+Dnv297D4jg3uECSNcY3MwH8D/PfM/CBwAfD5iPhgc2KpEXeuf57db/zaHYKkMa7uAs/MVzJzW+3zXwG7gJnNCjaa2tra3vL1gw8+yIoVKypK05j+/TozcZ9OaYxryhp4RMwGzgW2HOOxGyOiMyI6u7u7m3E4lwiO4+j9Ot2nUxrbGi7wiGgDvgPckpn7Bz+emaszsyMzO9rb2xs9HDC6SwRr165l0aJFnHvuuSxdupTXXnsNgJUrV3L99ddz4YUX8v73v5977rkHgI0bN7J48WKuvPJK5s6dy2c/+1mOHDnC/fffzy233DLwuvfccw+33nprU7P2z7779+vsPZzOwqUxrKECj4hJ9JX3w5n5WHMiHd9ILBEcPHiQhQsXDnx8+ctfHnjskksu4cc//jFPPfUU1157LXfcccfAY08//TRPPPEEmzdvZtWqVbz88ssAPPnkk9x1113s3LmTn//85zz22GNcc801rF27lt7eXgAeeOABPv3pTzec/WhHz777OQuXxq5GzkIJ4D5gV2b+XfMiHd9ILBFMnTqV7du3D3ysWrVq4LGuri4++tGPMn/+fL72ta+xY8eOgceWLVvG1KlTmTFjBpdddhlPPvkkAOeffz7vfe97mTBhAtdddx2bNm2ira2Nyy+/nHXr1vHcc8/R29vL/PnzG85+tMd3vTYw++7Xezh5fOerTT2OpNbQyIU8FwPXA89ExPba2G2Z+f2GUw1hqCWCv1ryPt55+pQROeZNN93EF77wBa6++mo2btzIypUrBx4bfNpf/9dDjX/mM5/h9ttv5wMf+ADLly9vetYtty1t+mtKal2NnIWyKTMjMxdk5sLax4iVN1SzRPDmm28yc2bfyTUPPfTQWx773ve+R09PD3v37mXjxo2cd955QN8SygsvvMCRI0d49NFHueSSSwBYtGgRu3fv5pFHHuG6664bscySxofKr8QcjiqWCFauXMknPvEJPvKRjzBjxoy3PLZgwQIuu+wyLrjgAr70pS9x5plnAnDeeeexYsUKzjnnHObMmcPHP/7xge+55ppruPjiiznjjDNGLLOk8aHye6EMx0gtERw4cOAtX99www3ccMMNQN8697Jly475fQsWLODrX//628bf8Y53sG7dumN+z6ZNm5p+9omk8amoGXjJ9u3bx9lnn83UqVNZsmRJ1XEkjQGRg9aUR1JHR0d2dna+ZWzXrl2cc845o5ah1fnzkDRYRGzNzI7B487AJalQFrgkFcoCl6RCWeCSVCgLHPjqV7/Khz70IRYsWMDChQvZsuVtN1U8phdffJF58+aNcDpJOraizgPn9plw6MDbxye3wW0v1fWSmzdvZt26dWzbto1TTjmF119/nUOHDjUYVJJGXlkFfqzyPt74SXjllVeYMWMGp5xyCsDA1ZarVq1i7dq1HDx4kIsuuoi7776biGDr1q0DdxG84oor6j6uJDVq3C+hXHHFFezevZuzzz6bz33uc/zoRz8CYMWKFfzkJz/h2Wef5eDBgwNXVi5fvpy77rqLn/70p1XGliQLvK2tja1bt7J69Wra29v55Cc/yYMPPsiGDRtYtGgR8+fP54knnmDHjh3s27ePffv2sXjxYgCuv/76itNLGs/KWkIZIRMmTODSSy/l0ksvZf78+dx99908/fTTdHZ2ctZZZ7Fy5Up6etzVRoK+2zr/2T9tZs1fXjhit3HWyRn3M/Cf/exnPP/88wNfb9++nblz5wJ96+EHDhxgzZo1AEybNo1p06axadMmAB5++OHRDyxVbDS3NNTxlTUDn9w29FkodTpw4AA33XQT+/btY+LEibzvfe9j9erVTJs2jXnz5vHud7974D7f8Nut0CLCNzE17gze0nAkN1PRiXkzqxbjz0Ot7H989xke7dxN7+Fk0oTgk+f9Pv/rY14LMdK8mZWkhgy1pWEzNhZXfSxwSSelii0NdXwtUeCjuYzTyvw5qJVVsaWhjq/yNzGnTJnC3r17mT59+tt2cx9PMpO9e/cyZYpvCKk1jdSWhqpf5QU+a9Ysurq66O7urjpK5aZMmcKsWbOqjiGpEJUX+KRJk5gzZ07VMSSpOC2xBi5JGj4LXJIKZYFLUqFG9UrMiOgGflHnt88AXm9inGYx1/CYa3jMNTxjNdcfZGb74MFRLfBGRETnsS4lrZq5hsdcw2Ou4RlvuVxCkaRCWeCSVKiSCnx11QGGYK7hMdfwmGt4xlWuYtbAJUlvVdIMXJJ0FAtckgrV8gUeEfdHxJ6IeLbqLEeLiLMiYkNE7IyIHRFxc9WZACJiSkQ8GRE/reX6n1Vn6hcREyLiqYhYV3WWo0XEixHxTERsj4jOE3/H6IiIaRGxJiKei4hdEXFhC2SaW/s59X/sj4hbqs4FEBG31v7OPxsR34iIlri1Z0TcXMu0o9k/q5ZfA4+IxcAB4OuZ2TJ7N0XEe4D3ZOa2iDgd2Ap8LDN3VpwrgNMy80BETAI2ATdn5o+rzAUQEV8AOoB3ZOZVVefpFxEvAh2Z2VIXgETEQ8D/zcx7I2IycGpm7qs41oCImAC8BCzKzHov0GtWlpn0/V3/YGYejIhvAd/PzAcrzjUP+CZwPnAI+AHw2cxsyi4YLT8Dz8x/Bf6j6hyDZeYrmbmt9vmvgF3AzGpTQfbp3/l5Uu2j8v+lI2IWcCVwb9VZShARvwssBu4DyMxDrVTeNUuAn1dd3keZCEyNiInAqcDLFecBOAfYkpm/zszfAD8C/muzXrzlC7wEETEbOBfYUnEUYGCpYjuwB3g8M1sh198Dfw0cqTjHsSTww4jYGhE3Vh2mZg7QDTxQW3a6NyJOqzrUINcC36g6BEBmvgT8LfBL4BXgzcz8YbWpAHgW+C8RMT0iTgX+FDirWS9ugTcoItqA7wC3ZOb+qvMAZObhzFwIzALOr/0aV5mIuArYk5lbq8xxHJdk5oeBPwE+X1u2q9pE4MPAP2bmucB/Al+sNtJv1ZZ0rga+XXUWgIg4A1hG3398ZwKnRcSnqk0FmbkL+D/AD+lbPtkOHG7W61vgDaitMX8HeDgzH6s6z2C1X7k3AH9ccZSLgatra83fBC6PiH+uNtJv1WZvZOYe4Lv0rVdWrQvoOuq3pzX0FXqr+BNgW2a+VnWQmqXAC5nZnZm9wGPARRVnAiAz78vMj2TmYuAN4P8167Ut8DrV3iy8D9iVmX9XdZ5+EdEeEdNqn08F/gh4rspMmfk3mTkrM2fT92v3E5lZ+ewIICJOq70JTW2J4gr6fu2tVGa+CuyOiLm1oSVApW+QD3IdLbJ8UvNL4IKIOLX2b3MJfe9LVS4i3ln78/fpW/9+pFmvXfmWaicSEd8ALgVmREQX8JXMvK/aVEDfrPJ64JnaejPAbZn5/eoiAfAe4KHaGQK/A3wrM1vqtL0W8y7gu7UNtScCj2TmD6qNNOAm4OHacsW/A8srzgMM/Ef3R8B/qzpLv8zcEhFrgG3Ab4CnaJ3L6r8TEdOBXuDzzXwzuuVPI5QkHZtLKJJUKAtckgplgUtSoSxwSSqUBS5JhbLAJalQFrgkFer/A3SizAl0ggmQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dict_data = {\n",
    "    'x_0':[7,3,2,1,2,4,1,8,6,7,8,9],\n",
    "    'x_1':[1,2,3,5,6,7,9,10,5,8,4,6],\n",
    "    'y': [0,0,0,0,0,0,1,1,1,1,1,1]\n",
    "    }\n",
    "data = pandas.DataFrame(dict_data)\n",
    "\n",
    "columns_features = ['x_0', 'x_1']\n",
    "features = data[columns_features].values\n",
    "labels = data['y'].values\n",
    "\n",
    "# Plot the original set\n",
    "_plotting.plot_scatter(data['x_0'][labels == 0], data['x_1'][labels == 0], marker = '^')\n",
    "_plotting.plot_scatter(data['x_0'][labels == 1], data['x_1'][labels == 1], marker = 's')\n",
    "plt.legend([\"Happy\", \"Sad\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd4c2496-6294-44dc-afa4-44a5dba945bb",
   "metadata": {},
   "source": [
    "## Building a decision tree using Gini index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6de685bc-ca7b-46d2-b024-6a5888fd5312",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decision_tree = sklearn.tree.DecisionTreeClassifier() # Defaults to gini index\n",
    "decision_tree.fit(features, labels)\n",
    "decision_tree.score(features, labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "63ab65f9-9b19-4d1e-9b35-8fa294be984b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0.8333333333333334, 'x_0 <= 5.0\\ngini = 0.5\\nsamples = 12\\nvalue = [6, 6]'),\n",
       " Text(0.25, 0.5, 'x_1 <= 8.0\\ngini = 0.278\\nsamples = 6\\nvalue = [5, 1]'),\n",
       " Text(0.125, 0.16666666666666666, 'gini = 0.0\\nsamples = 5\\nvalue = [5, 0]'),\n",
       " Text(0.375, 0.16666666666666666, 'gini = 0.0\\nsamples = 1\\nvalue = [0, 1]'),\n",
       " Text(0.75, 0.5, 'x_1 <= 2.5\\ngini = 0.278\\nsamples = 6\\nvalue = [1, 5]'),\n",
       " Text(0.625, 0.16666666666666666, 'gini = 0.0\\nsamples = 1\\nvalue = [1, 0]'),\n",
       " Text(0.875, 0.16666666666666666, 'gini = 0.0\\nsamples = 5\\nvalue = [0, 5]')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn.tree.plot_tree(decision_tree, feature_names=columns_features, filled=True, rounded=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "99396586-6e7c-4aee-81d8-a8d2c7db9950",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_plotting.plot_decision_boundary_2D(features, labels, decision_tree)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0ff0592-ca94-4163-8681-5ece234a18e4",
   "metadata": {},
   "source": [
    "## Building a decision tree using entropy\n",
    "\n",
    "#### How does it compare with the Gini index?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "19185b05-2d53-4f6b-88f7-304f8a8c30cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decision_tree_entropy = sklearn.tree.DecisionTreeClassifier(criterion='entropy')\n",
    "decision_tree_entropy.fit(features, labels)\n",
    "decision_tree_entropy.score(features, labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3b098129-82a6-4d02-a2a1-3cd229ecd5af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0.8333333333333334, 'x_0 <= 5.0\\nentropy = 1.0\\nsamples = 12\\nvalue = [6, 6]'),\n",
       " Text(0.25, 0.5, 'x_1 <= 8.0\\nentropy = 0.65\\nsamples = 6\\nvalue = [5, 1]'),\n",
       " Text(0.125, 0.16666666666666666, 'entropy = 0.0\\nsamples = 5\\nvalue = [5, 0]'),\n",
       " Text(0.375, 0.16666666666666666, 'entropy = 0.0\\nsamples = 1\\nvalue = [0, 1]'),\n",
       " Text(0.75, 0.5, 'x_1 <= 2.5\\nentropy = 0.65\\nsamples = 6\\nvalue = [1, 5]'),\n",
       " Text(0.625, 0.16666666666666666, 'entropy = 0.0\\nsamples = 1\\nvalue = [1, 0]'),\n",
       " Text(0.875, 0.16666666666666666, 'entropy = 0.0\\nsamples = 5\\nvalue = [0, 5]')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn.tree.plot_tree(decision_tree_entropy, feature_names=columns_features, filled=True, rounded=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bb0b213b-d9f8-4913-83fc-f0142aa7e4e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWYAAAD8CAYAAABErA6HAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAWnElEQVR4nO3df7DdZWHn8fcnNz+BLARjXUyyIczG1igbsLfgCouM+COok3Sr2wkda3BtM46kpVa3hc4Ku3F0sWNtaU1Z72BaXX/ETGTYrBuMjJA6rYC5YAok7MVL+JF7iYuYEKybHzfJZ/8430tPbu695+Sck5zvPffzmrlzz/f5Pt/nec5APvnm+f54ZJuIiCiPKe0eQEREnCjBHBFRMgnmiIiSSTBHRJRMgjkiomQSzBERJZNgjoioQdJ6SS9IenyM/ZL0l5L6JT0q6U1V+45J2lH8bK6nvwRzRERtfwssG2f/tcDi4mc1cEfVvoO2Lyl+ltfTWYI5IqIG298H9o1TZQXwFVc8CJwn6YJG+5va6IGNmDLjHE89+1VnssuImKCG9j/3ou1XN3r8zAve4OOH/6nevnYCh6qKemz3nEJ384A9VdsDRdleYKakXuAocJvtu2s1dkaDeerZr2LuO246k11GxAS1d+NHn23m+OOH/6nuvNm78aOHbHc30984FtoelHQRcJ+kx2w/Nd4BmcqIiGjeILCgant+UYbt4d+7gW3ApbUaSzBHRDRvM/DB4u6MNwMHbO+VNEfSDABJc4ErgF21GjujUxkRERORpG8AVwNzJQ0AtwLTAGz/d2AL8G6gH/h/wIeKQ18PfFHScSonwrfZTjBHRDTL9nU19hu4YZTyHwAXn2p/mcqIiCiZBHNERMkkmCMiSibBHBFRMgnmiIiSSTBHRJRMgjkiomQSzBERJZNgjogomZrBPNqb+yWdL+leST8ufs85vcOMiPEcO3iA/d+5hWMHD7R7KNEC9Zwx/y0nv7n/JuB7thcD3yu2I6JNhvruYcaRfQw9eU+7hxItUDOYx3hz/wrgy8XnLwO/3tphRUS9jh08wKFnH+D+D87i8DMP5Ky5AzQ6x/wa23uLzz8BXjNWRUmrJfVK6q13NYGIqN9Q3z1cv3Qql17QxaqlU3PW3AGavvhXvFXJ4+zvsd1tu3vKjHOa7S4iqgyfLX/yyi4APnllV86aO0Cjwfx/hxcaLH6/0LohRUS9hs+WL5hd+aN8wewpOWvuAI2+j3kzsAq4rfj9P1s2ooio26HnH+WOJw9yxw8PnlA+65xHmbl0ZZtGFc2qGcxjvLn/NmCjpA8DzwK/eToHGRGjO+/dn+G8dg8iWq5mMI/z5v5rWjyWiIggT/5FRJROgjkiomQSzBERJZNgjogomQRzREQdJC2T1CepX9JJ7weStFDS9yQ9KmmbpPlV+1YVL337saRVtfpKMEdE1CCpC1gHXAssAa6TtGREtc8BX7H9b4C1wH8rjj2fym3GlwOXAbfWeiNngjkiorbLgH7bu20fATZQeZlbtSXAfcXn+6v2vwu41/Y+2/uBezn5jZ0naPTJv4iIUjtr9ln86jWX1FX32xuZK6m3qqjHdk/V9jxgT9X2AJUz4Gr/CPwGcDvw74HZkl41xrHzxhtPgjkiAl603d1kG58AviDpeuD7wCBwrJGGEswREbUNAguqtucXZa+w/TyVM2YknQO8z/ZLkgapvNai+tht43WWOeaIiNq2A4slLZI0HVhJ5WVur5A0V9Jwpt4MrC8+bwXeKWlOcdHvnUXZmDoymLP+WUS0ku2jwBoqgfoEsNH2TklrJS0vql0N9El6ksriIZ8ujt0HfIpKuG8H1hZlY+rIqYzq9c+68urDiGgB21uALSPKbqn6vAnYNMax6/nnM+iaOu6MOeufRcRE13HBnPXPImKi66hgzvpnEdEJOiqYs/5ZRHSCjrr4l/XPIqITdFQwZ/2ziOgEHTWVERHRCRLMERElk2COiCiZBHNERMkkmCMiSibBHBFRMgnmiIiSSTBHRJRMgjkiomQSzBERJZNgjogomQRzRETJNBXMkj4maaekxyV9Q9LMVg0sYqLL2pPRqIaDWdI84PeBbttvBLqorBwbEZy49mTEqWj2tZ9TgVmShoCzgOfHq7zwtefxl//1N5rsMjrRh2+9q91DaKnh1XT+YdUsrvzyA0x73bV0zTq33cOKCaLhYLY9KOlzwHPAQeC7tr87sp6k1cBqgPOnTOX5t7y10S6jgz3zv9byvp0LePh7O9o9lJYYufbkhqzYHqegmamMOcAKYBHwWuBsSR8YWc92j+1u292z1dX4SKPjffSqi9o9hJbI2pOdSdIySX2S+iXdNMr+P5e0o/h5UtJLVfuOVe3bXKuvZi7+vR142vZPbQ8BdwFvaaK9iI6QtSc7j6QuYB1wLbAEuE7Skuo6tj9m+xLblwB/RSUThx0c3md7ea3+mpljfg54s6SzqExlXAP0NtFeREfI2pMd6TKg3/ZuAEkbqMwY7Bqj/nXArY121swc80OSNgGPAEeBHwE9jbYX0Smy9mQ5vHr29Lqnx74NcyVVn1j22K7Os3nAnqrtAeDy0dqStJDKFO99VcUzi/aPArfZvnu88TR1V4btW2nib4WIiJJ40XZ3i9paCWyyfayqbGFxw8RFwH2SHrP91FgN5Mm/iIjaBoEFVdvzi7LRrAS+UV1ge7D4vRvYBlw6XmcJ5oiI2rYDiyUtkjSdSviedHeFpF8B5gAPVJXNkTSj+DwXuIKx56aB5h8wiYjoeLaPSloDbKXylPN62zslrQV6bQ+H9Epgg21XHf564IuSjlM5Gb7NdoI5IqJZtrcAW0aU3TJi+7+MctwPgItPpa9MZURElEyCOSKiZBLMERElk2COiCiZBHNERMkkmCMiSibBHBFRMrmPOU6w5sBuDh0fOql85pRpfOHcznhfckTZJZjjBIeOD7Hwj799Uvmzn31vG0YTMTllKiMiomQSzBERJZNgjogomQRzRETJ5OJfnGDmlGmjXuibOWVaG0YTMTklmOMEuSUuov0ylRERUTIJ5oiIkkkwR0SUTII5IqJkEswRESWTYI6IKJkEc0REySSYIyLqIGmZpD5J/ZJuGqPOb0raJWmnpK9Xla+S9OPiZ1WtvvKASUREDZK6gHXAO4ABYLukzbZ3VdVZDNwMXGF7v6RfKsrPB24FugEDDxfH7h+rv5wxR0TUdhnQb3u37SPABmDFiDq/C6wbDlzbLxTl7wLutb2v2HcvsGy8zhLMERG1zQP2VG0PFGXVXge8TtI/SHpQ0rJTOPYEmcqIiI40e8ZUrr7w3Hqrz5XUW7XdY7vnFLucCiwGrgbmA9+XdPEptvFKQw2TdB5wJ/BGKnMn/9H2A820OVFkbbyYrI4dPMDLf/dn/Iu3fpyuWXUHX9m9aLt7nP2DwIKq7flFWbUB4CHbQ8DTkp6kEtSDVMK6+tht4w2m2TPm24Hv2H6/pOnAWU22N2FkbbyYrIb67mHGkX0MPXkPXUtXtns4Z8p2YLGkRVSCdiXwWyPq3A1cB/yNpLlUpjZ2A08Bn5E0p6j3TioXCcfU8ByzpHOBq4AvAdg+YvulRtuLiPI7dvAAh559gPs/OIvDzzzAsYMH2j2kM8L2UWANsBV4Athoe6ektZKWF9W2Aj+TtAu4H/hPtn9mex/wKSrhvh1YW5SNqZkz5kXAT6n87bAUeBi40fYvqitJWg2sBjh/Sqa0Iyayob57uH7pVC69oItVS6eyYRKdNdveAmwZUXZL1WcDf1j8jDx2PbC+3r6auStjKvAm4A7blwK/AE666dp2j+1u292z1dVEdxHRTsNny5+8svLn+JNXdk2qs+YzqZlgHgAGbD9UbG+iEtQR0YGGz5YvmF2JjQtmT2HV0qkMPXlPm0fWeRqeW7D9E0l7JP2y7T7gGmBXreM6RdbGi8nm0POPcseTB7njhwdPKJ91zqPMnCTTGWdKs5O+vwd8rbgjYzfwoeaHNDHklriYbM5792c4r92DmCSaCmbbO6g8/x0RES2SR7IjIkomwRwRUTIJ5oiIkkkwR0SUTII5IqJkEswRESWTYI6IKJkEc0REySSYIyJKJsEcEVEyCeaIiJLpqDfXZx2+qKVD16uLDtNRwZx1+KKWSbpeXUwwmcqISWOyrlcXE0+COSaNkevVZeWNKKsEc0wKWa8uJpIEc0wKWa8uJpKOuviXdfhiLFmvLpolaRlwO9AF3Gn7tjHqvY/K4tS/ZrtX0oXAE0BfUeVB2x8Zr6+OCubcEhdjyXp10QxJXcA64B3AALBd0mbbu0bUmw3cCDw0oomnbF9Sb3+ZyoiIqO0yoN/2bttHgA3AilHqfQr4LHComc4SzBERtc0D9lRtDxRlr5D0JmCB7f89yvGLJP1I0t9J+ne1OuuoqYyIiGH6xUt0Pby53upzJfVWbffY7qm7L2kK8Hng+lF27wX+le2fSfpV4G5Jb7D98ljtJZgjIuBF293j7B8EFlRtzy/Khs0G3ghskwTwL4HNkpbb7gUOA9h+WNJTwOuA6r8ITpCpjIiI2rYDiyUtkjQdWAm8cjpu+4DtubYvtH0h8CCwvLgr49XFxUMkXQQsBnaP11nOmCMiarB9VNIaYCuV2+XW294paS3Qa3u8OZOrgLWShoDjwEds7xuvvwRzREQdbG8Btowou2WMuldXff4W8K1T6StTGRERJZNgjogomQRzRETJJJgjIkomwRwRUTJNB7OkruJRw5PXdIqIM+LYwQPs/84teb90h2jFGfONVF5pFxFtUr2WYUx8TQWzpPnAe4A7WzOciDhVWcuw8zR7xvwXwB9ReZplVJJWS+qV1PtzH2uyu4gYKWsZdp6Gg1nSe4EXbD88Xj3bPba7bXfPrjwuHhEtkrUMO1MzZ8xXAMslPUPlpdFvk/TVlowqIuqStQw7U8PvyrB9M3AzgKSrgU/Y/kBrhhUR9chahp0pLzGKmMCylmFnakkw294GbGtFWxERk12e/IuIKJkEc0REySSYIyJKJsEcEVEyCeaIiJJJMEdElEyCOSKiZBLMERElk2COiCiZBHNERB0kLZPUJ6lf0k2j7P+IpMck7ZD095KWVO27uTiuT9K7avWVYI6IqEFSF7AOuBZYAlxXHbyFr9u+2PYlwJ8Cny+OXQKsBN4ALAP+umhvTHmJUYPWHNjNoeNDJ5XPnDKNL5x7URtGFBGn0WVAv+3dAJI2ACuAXcMVbL9cVf9swMXnFcAG24eBpyX1F+09MFZnCeYGHTo+xMI/Pnn92Wc/+942jCYiRjqybx/PfnVjvdXnSuqt2u6x3VO1PQ/YU7U9AFw+shFJNwB/CEwH3lZ17IMjjp033mASzBER8KLt7mYbsb0OWCfpt4D/DKxqpJ3MMUdE1DYILKjanl+UjWUD8OsNHptgjoiow3ZgsaRFkqZTuZi3ubqCpMVVm+8Bflx83gyslDRD0iJgMfDD8TrLVEZERA22j0paA2wFuoD1tndKWgv02t4MrJH0dmAI2E8xjVHU20jlQuFR4Abbx8brL8HcoJlTpo16oW/mlGltGE1EnG62twBbRpTdUvX5xnGO/TTw6Xr7SjA3KLfERcTpkjnmiIiSSTBHRJRMgjkiomQSzFEKp/CEVkTHy8W/KIXvf/Nx+OZbeer5He0eSpTEWRs/2u4htE2COUrl66+9pN1DiGi7TGVERJRMgjkiomQSzBERJZNgjogomQRzRETJJJgjIkqm4dvlJC0AvgK8hsraVj22b2/VwOKfZX3BiMmlmfuYjwIft/2IpNnAw5Lutb2r1oFxarK+YMTk0vBUhu29th8pPv8ceIIaCwxGRERtLXnyT9KFwKXAQ6PsWw2sBjh/Sh40jIiopemLf5LOAb4F/IHtl0fut91ju9t292x1NdtdRETHayqYJU2jEspfs31Xa4YUETG5NXNXhoAvAU/Y/nzrhhQjZX3BiMmlmUnfK4DfBh6TtKMo+5NiwcJoodwSFzG5NBzMtv8eUAvHEhER5Mm/iIi6SFomqU9Sv6SbRtl/laRHJB2V9P4R+45J2lH8bK7VV+5fi4ioQVIXsA54BzAAbJe0ecQDdc8B1wOfGKWJg7Yvqbe/BHNERG2XAf22dwNI2gCsAF4JZtvPFPuON9tZgjkiOtLP9x2srCVZn7mSequ2e2z3VG3PA/ZUbQ8Al5/CcGYW7R8FbrN993iVE8wREfCi7e7T2P5C24OSLgLuk/SY7afGqpyLfxERtQ0CC6q25xdldbE9WPzeDWyj8gqLMSWYIyJq2w4slrRI0nRgJVDz7goASXMkzSg+z6XyDMi4b+FMMEdE1GD7KLAG2ErlTZobbe+UtFbScgBJvyZpAPgPwBcl7SwOfz3QK+kfgfupzDGPG8yZY46IqEPxVPOWEWW3VH3eTmWKY+RxPwAuPpW+csYcEVEyCeaIiJLJVEZEi2WNxmhWgjmixbJGYzQrUxkRESWTYI6IKJkEc0REySSYIyJKJhf/IlosazRGsxLMES2WW+KiWZnKiIgomQRzRETJJJgjIkomwRwRUTIJ5oiIkkkwR0SUTII5IqJkEswRESWTYI6IKJkEc0REySSYIyJKJsEcEVEyTQWzpGWS+iT1S7qpVYOKiCibWnknaYakbxb7H5J0YdW+m4vyPknvqtVXw8EsqQtYB1wLLAGuk7Sk0fYiIsqqzrz7MLDf9r8G/hz4bHHsEmAl8AZgGfDXRXtjauaM+TKg3/Zu20eADcCKJtqLiCirevJuBfDl4vMm4BpJKso32D5s+2mgv2hvTM28j3kesKdqewC4fGQlSauB1cXm4d/Z3/d4E32W1VzgxXYP4jTI95pYOu17LWzm4GePHd76O/v75tZZfaak3qrtHts9Vdv15N0rdWwflXQAeFVR/uCIY+eNN5jT/qL84sv1AEjqtd19uvs80/K9JpZ8r8nB9rJ2j6FRzUxlDAILqrbnF2UREZ2mnrx7pY6kqcC5wM/qPPYEzQTzdmCxpEWSplOZ3N7cRHsREWVVT95tBlYVn98P3GfbRfnK4q6NRcBi4IfjddbwVEYxh7IG2Ap0Aett76xxWE+N/RNVvtfEku8Vp2SsvJO0Fui1vRn4EvA/JPUD+6iEN0W9jcAu4Chwg+1j4/WnSqBHRERZ5Mm/iIiSSTBHRJTMGQnmTnx0W9ICSfdL2iVpp6Qb2z2mVpLUJelHkr7d7rG0kqTzJG2S9H8kPSHp37Z7TK0g6WPF/4ePS/qGpJntHlM07rQHcwc/un0U+LjtJcCbgRs65HsNuxF4ot2DOA1uB75j+1eApXTAd5Q0D/h9oNv2G6lcnFrZ3lFFM87EGXNHPrpte6/tR4rPP6fyB3zcp3kmCknzgfcAd7Z7LK0k6VzgKipXz7F9xPZLbR1U60wFZhX3z54FPN/m8UQTzkQwj/YoY0cE2LDiLVKXAg+1eSit8hfAHwHH2zyOVlsE/BT4m2Ka5k5JZ7d7UM2yPQh8DngO2AscsP3d9o4qmpGLf02SdA7wLeAPbL/c7vE0S9J7gRdsP9zusZwGU4E3AXfYvhT4BTDhr3lImkPlX6GLgNcCZ0v6QHtHFc04E8HcsY9uS5pGJZS/Zvuudo+nRa4Alkt6hsq009skfbW9Q2qZAWDA9vC/bDZRCeqJ7u3A07Z/ansIuAt4S5vHFE04E8HckY9uF6/z+xLwhO3Pt3s8rWL7ZtvzbV9I5b/VfbY74uzL9k+APZJ+uSi6hsrTWBPdc8CbJZ1V/H95DR1wUXMyOxNvl2vk0e2J4Argt4HHJO0oyv7E9pb2DSnq8HvA14qThN3Ah9o8nqbZfkjSJuARKncL/Yg8nj2h5ZHsiIiSycW/iIiSSTBHRJRMgjkiomQSzBERJZNgjogomQRzRETJJJgjIkrm/wN9be9v84gaDQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_plotting.plot_decision_boundary_2D(features, labels, decision_tree_entropy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a4231a6-36a5-45c7-a48c-2359874b02a1",
   "metadata": {},
   "source": [
    "## Building a decision tree of depth one (a vertical or horizontal line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ca804d85-0d13-42af-a330-0a78a17d9b2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8333333333333334"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decision_tree_depth_1 = sklearn.tree.DecisionTreeClassifier(max_depth=1)\n",
    "decision_tree_depth_1.fit(features, labels)\n",
    "decision_tree_depth_1.score(features, labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ffb61513-f449-43dc-b4eb-30127bf26ac3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0.75, 'x_0 <= 5.0\\ngini = 0.5\\nsamples = 12\\nvalue = [6, 6]'),\n",
       " Text(0.25, 0.25, 'gini = 0.278\\nsamples = 6\\nvalue = [5, 1]'),\n",
       " Text(0.75, 0.25, 'gini = 0.278\\nsamples = 6\\nvalue = [1, 5]')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn.tree.plot_tree(decision_tree_depth_1, feature_names=columns_features, filled=True, rounded=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4620b5b1-d2f7-4749-865c-9fd44cbf0b84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_plotting.plot_decision_boundary_2D(features, labels, decision_tree_depth_1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
